research
∙
01/02/2021
Context-Aware Safe Reinforcement Learning for Non-Stationary Environments
Safety is a critical concern when deploying reinforcement learning agent...
share
research
∙
10/15/2020
Safe Model-based Reinforcement Learning with Robust Cross-Entropy Method
This paper studies the safe reinforcement learning (RL) problem without ...
research
∙
09/16/2020
Multimodal Safety-Critical Scenarios Generation for Decision-Making Algorithms Evaluation
Existing neural network-based autonomous systems are shown to be vulnera...
research
∙
07/30/2020
MAPPER: Multi-Agent Path Planning with Evolutionary Reinforcement Learning in Mixed Dynamic Environments
Multi-agent navigation in dynamic environments is of great industrial va...
research
∙
06/19/2020
Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes
Continuously learning to solve unseen tasks with limited experience has ...
research
∙
05/11/2020
Delay-Aware Multi-Agent Reinforcement Learning for Cooperative and Competitive Environments
Action and observation delays exist prevalently in the real-world cyber-...
research
∙
05/11/2020
Delay-Aware Model-Based Reinforcement Learning for Continuous Control
Action delays degrade the performance of reinforcement learning in many ...
research
∙
04/14/2020
